Search results for: auditory processing delays

Authors: Zahra Ahmadi, Fazlollah Adibnia

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Scheduling of tasks and the optimal allocation of resources in the cloud are based on the dynamic nature of tasks and the heterogeneity of resources. Applications that are based on the scientific workflow are among the most widely used applications in this field, which are characterized by high processing power and storage capacity. In order to increase their efficiency, it is necessary to plan the tasks properly and select the best virtual machine in the cloud. The goals of the system are effective factors in scheduling tasks and resource selection, which depend on various criteria such as time, cost, current workload and processing power. Multi-criteria decision-making methods are a good choice in this field. In this research, a new method of work planning and resource allocation in a heterogeneous environment based on the modified AHP algorithm is proposed. In this method, the scheduling of input tasks is based on two criteria of execution time and size. Resource allocation is also a combination of the AHP algorithm and the first-input method of the first client. Resource prioritization is done with the criteria of main memory size, processor speed and bandwidth. What is considered in this system to modify the AHP algorithm Linear Max-Min and Linear Max normalization methods are the best choice for the mentioned algorithm, which have a great impact on the ranking. The simulation results show a decrease in the average response time, return time and execution time of input tasks in the proposed method compared to similar methods (basic methods).

Keywords: hierarchical analytical process, work prioritization, normalization, heterogeneous resource allocation, scientific workflow

Procedia PDF Downloads 131

Authors: Charisse H. Tay

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Background: Schizophrenia is a severe chronic mental disorder that can result in hallucinations, delusions, reduced social engagement, and lack of motivation. While antipsychotic medications often provide the basis for treatment, psychosocial strategies complement the benefit of medications and can result in meaningful improvements in symptoms and functioning. The aim of the study was to investigate psychosocial strategies used by internet self-help forum participants to effectively manage symptoms caused by schizophrenia. Internet self-help forums are a resource for medical and psychological problems and are commonly used to share information about experiences with symptom management. Method: Three international self-help internet forums on schizophrenia were identified using a search engine. 1,181 threads regarding non-pharmacological, psychosocial self-management of schizophrenia symptoms underwent screening, resulting in the final identification and coding of 91 threads and 191 posts from 134 unique forum users that contained details on psychosocial strategies endorsed personally by users that allowed them to effectively manage symptoms of schizophrenia, including positive symptoms (e.g., auditory/visual/tactile hallucinations, delusions, paranoia), negative symptoms (e.g.., avolition, apathy, anhedonia), symptoms of distress, and cognitive symptoms (e.g., memory loss). Results: Effective symptom management strategies personally endorsed by online forum users were psychological skills (e.g., re-focusing, mindfulness/meditation, reality checking; n = 94), engaging in activities (e.g., exercise, working/volunteering, hobbies; n = 84), social/familial support (n = 48), psychotherapy (n = 33), diet (n = 18), and religion/spirituality (n = 14). 44.4% of users reported using more than one strategy to manage their symptoms. The most common symptoms targeted and effectively managed, as specified by users, were positive symptoms (n = 113), negative symptoms (n = 17), distress (n = 8), and memory loss (n = 6). 10.5% of users reported more than one symptom effectively targeted. 70.2% of users with positive symptoms reported that psychological skills were effective for symptom relief. 88% of users with negative symptoms and 75% with distress symptoms reported that engaging in activities was effective. Discussion: Individuals with schizophrenia rely on a variety of different psychosocial methods to manage their symptoms. Different symptomology appears to be more effectively targeted by different types of psychosocial strategies. This may help to inform treatment strategy and tailored for individuals with schizophrenia.

Keywords: psychosocial treatment, qualitative methods, schizophrenia, symptom management

Procedia PDF Downloads 111

Authors: Daniel Pinheiro Da Silva Junior, Aline Paes, Daniel De Oliveira, Christiano Lacerda Ghuerren, Marcio Duran

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The Courts of Accounts are institutions responsible for overseeing and point out irregularities of Public Administration expenses. They have a high demand for processes to be analyzed, whose decisions must be grounded on severity laws. Despite the existing large amount of processes, there are several cases reporting similar subjects. Thus, previous decisions on already analyzed processes can be a precedent for current processes that refer to similar topics. Identifying similar topics is an open, yet essential task for identifying similarities between several processes. Since the actual amount of topics is considerably large, it is tedious and error-prone to identify topics using a pure manual approach. This paper presents a tool based on Machine Learning and Natural Language Processing to assists in building a labeled dataset. The tool relies on Topic Modelling with Latent Dirichlet Allocation to find the topics underlying a document followed by Jensen Shannon distance metric to generate a probability of similarity between documents pairs. Furthermore, in a case study with a corpus of decisions of the Rio de Janeiro State Court of Accounts, it was noted that data pre-processing plays an essential role in modeling relevant topics. Also, the combination of topic modeling and a calculated distance metric over document represented among generated topics has been proved useful in helping to construct a labeled base of similar and non-similar document pairs.

Keywords: courts of accounts, data labelling, document similarity, topic modeling

Procedia PDF Downloads 159

Authors: Krystian Szczepanski, Sylwia Łaba

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Production of fruit and vegetables, food cereals or oilseeds affects the natural environment via intake of nutrients being contained in the soil, use of the resources of water, fertilizers and food protection products, and energy. The limitation of the mentioned effects requires the introduction of techniques and methods for cultivation being friendly to the environment and counteracting losses and waste of agricultural raw materials as well as the appropriate management of food waste in every stage of the agri-food supply chain. The link to basic production includes obtaining a vegetal raw material and its storage in agricultural farm and transport to a collecting point. When the plants are ready to be harvested is the initial point; the stage before harvesting is not considered in the system of measuring and monitoring the food losses. The moment at which the raw material enters the stage of processing, i.e., its receipt at the gate of the processing plant, is considered as a final point of basic production. According to the Regulation (EC) No 178/2002 of the European Parliament and of the Council of 28 January 2002, Art. 2, “food” means any substance or product, intended to be, or reasonably expected to be consumed by humans. For the needs of the studies and their analysis, it was determined when raw material is considered as food – the plants (fruit, vegetables, cereals, oilseeds), after being harvested, arrive at storehouses. The aim of the studies was to determine the reasons for loss generation and to analyze the directions of their management in basic vegetal production in Poland in the years 2017 and 2018. The studies on food losses and waste in basic vegetal production were carried out in three sectors – fruit and vegetables, cereals and oilseeds. The studies of the basic production were conducted during the period of March-May 2019 at the territory of the whole country on a representative trail of 250 farms in each sector. The surveys were carried out using the questionnaires by the PAP method; the pollsters conducted the direct questionnaire interviews. From the conducted studies, it is followed that in 19% of the examined farms, any losses were not recorded during preparation, loading, and transport of the raw material to the manufacturing plant. In the farms, where the losses were indicated, the main reason in production of fruit and vegetables was rotting and it constituted more than 20% of the reported reasons, while in the case of cereals and oilseeds’ production, the respondents identified damages, moisture and pests as the most frequent reason. The losses and waste, generated in vegetal production as well as in processing and trade of fruit and vegetables, or cereal products should be appropriately managed or recovered. The respondents indicated composting (more than 60%) as the main direction of waste management in all categories. Animal feed and landfill sites were the other indicated directions of management. Prevention and minimization of loss generation are important in every stage of production as well as in basic production. When possessing the knowledge on the reasons for loss generation, we may introduce the preventive measures, mainly connected with the appropriate conditions and methods of the storage. Production of fruit and vegetables, food cereals or oilseeds affects the natural environment via intake of nutrients being contained in the soil, use of the resources of water, fertilizers and food protection products, and energy. The limitation of the mentioned effects requires the introduction of techniques and methods for cultivation being friendly to the environment and counteracting losses and waste of agricultural raw materials as well as the appropriate management of food waste in every stage of the agri-food supply chain. The link to basic production includes obtaining a vegetal raw material and its storage in agricultural farm and transport to a collecting point. The starting point is when the plants are ready to be harvested; the stage before harvesting is not considered in the system of measuring and monitoring the food losses. The successive stage is the transport of the collected crops to the collecting point or its storage and transport. The moment, at which the raw material enters the stage of processing, i.e. its receipt at the gate of the processing plant, is considered as a final point of basic production. Processing is understood as the change of the raw material into food products. According to the Regulation (EC) No 178/2002 of the European Parliament and of the Council of 28 January 2002, Art. 2, “food” means any substance or product, intended to be, or reasonably expected to be consumed by humans. It was determined (for the needs of the present studies) when raw material is considered as a food; it is the moment when the plants (fruit, vegetables, cereals, oilseeds), after being harvested, arrive at storehouses. The aim of the studies was to determine the reasons for loss generation and to analyze the directions of their management in basic vegetal production in Poland in the years 2017 and 2018. The studies on food losses and waste in basic vegetal production were carried out in three sectors – fruit and vegetables, cereals and oilseeds. The studies of the basic production were conducted during the period of March-May 2019 at the territory of the whole country on a representative trail of 250 farms in each sector. The surveys were carried out using the questionnaires by the PAPI (Paper & Pen Personal Interview) method; the pollsters conducted the direct questionnaire interviews. From the conducted studies, it is followed that in 19% of the examined farms, any losses were not recorded during preparation, loading, and transport of the raw material to the manufacturing plant. In the farms, where the losses were indicated, the main reason in production of fruit and vegetables was rotting and it constituted more than 20% of the reported reasons, while in the case of cereals and oilseeds’ production, the respondents identified damages, moisture, and pests as the most frequent reason. The losses and waste, generated in vegetal production as well as in processing and trade of fruit and vegetables, or cereal products should be appropriately managed or recovered. The respondents indicated composting (more than 60%) as the main direction of waste management in all categories. Animal feed and landfill sites were the other indicated directions of management. Prevention and minimization of loss generation are important in every stage of production as well as in basic production. When possessing the knowledge on the reasons for loss generation, we may introduce the preventive measures, mainly connected with the appropriate conditions and methods of the storage. ACKNOWLEDGEMENT The article was prepared within the project: "Development of a waste food monitoring system and an effective program to rationalize losses and reduce food waste", acronym PROM implemented under the STRATEGIC SCIENTIFIC AND LEARNING PROGRAM - GOSPOSTRATEG financed by the National Center for Research and Development in accordance with the provisions of Gospostrateg1 / 385753/1/2018

Keywords: food losses, food waste, PAP method, vegetal production

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Authors: Andressa S. T. Gomes, Luiza A. Souza, Luciana H. Yamane, Renato R. Siman

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The segregation of waste of electrical and electronic equipment (WEEE) in the generating source, its characterization (quali-quantitative) and identification of origin, besides being integral parts of classification reports, are crucial steps to the success of its integrated management. The aim of this paper was to count WEEE generation at the Federal University of Espírito Santo (UFES), Brazil, as well as to define sources, temporary storage sites, main transportations routes and destinations, the most generated WEEE and its recycling potential. Quantification of WEEE generated at the University in the years between 2010 and 2015 was performed using data analysis provided by UFES’s sector of assets management. EEE and WEEE flow in the campuses information were obtained through questionnaires applied to the University workers. It was recorded 6028 WEEEs units of data processing equipment disposed by the university between 2010 and 2015. Among these waste, the most generated were CRT screens, desktops, keyboards and printers. Furthermore, it was observed that these WEEEs are temporarily stored in inappropriate places at the University campuses. In general, these WEEE units are donated to NGOs of the city, or sold through auctions (2010 and 2013). As for recycling potential, from the primary processing and further sale of printed circuit boards (PCB) from the computers, the amount collected could reach U$ 27,839.23. The results highlight the importance of a WEEE management policy at the University.

Keywords: solid waste, waste of electrical and electronic equipment, waste management, institutional solid waste generation

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Authors: Gobinathan Devathasan, Kezia Devathasan

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Objective: To improve the current modified Broca-Wernicke-Lichtheim-Kussmaul speech schema and provide insight into autism. Methods: We reviewed the pertinent literature. Current findings, involving Brodmann areas 22, 46, 9,44,45,6,4 are based on neuropathology and functional MRI studies. However, in primary autism, there is no lucid explanation and changes described, whether neuropathology or functional MRI, appear consequential. Findings: We forward an enhanced model which may explain the enigma related to autism. Vowel output is subcortical and does need cortical representation whereas consonant speech is cortical in origin. Left lateralization is needed to commence the circuitry spin as our life have evolved with L-amino acids and left spin of electrons. A fundamental species difference is we are capable of three syllable-consonants and bi-syllable expression whereas cetaceans and songbirds are confined to single or dual consonants. The 4 key sites for speech are superior auditory cortex, Broca’s two areas, and the supplementary motor cortex. Using the Argand’s diagram and Reimann’s projection, we theorize that the Euclidean three dimensional synaptic neuronal circuits of speech are quantized to coherent waves, and then decoherence takes place at area 6 (spherical representation). In this quantum state complex, 3-consonant languages are instantaneously integrated and multiple languages can be learned, verbalized and differentiated. Conclusion: We postulate that evolutionary human speech is elevated to quantum interaction unlike cetaceans and birds to achieve the three consonants/bi-syllable speech. In classical primary autism, the sudden speech switches off and on noted in several cases could now be explained not by any anatomical lesion but failure of coherence. Area 6 projects directly into prefrontal saccadic area (8); and this further explains the second primary feature in autism: lack of eye contact. The third feature which is repetitive finger gestures, located adjacent to the speech/motor areas, are actual attempts to communicate with the autistic child akin to sign language for the deaf.

Keywords: quantum neuronal paradigm, cetaceans and human speech, autism and rapid magnetic stimulation, coherence and decoherence of speech

Procedia PDF Downloads 175

Authors: Yahya Almurtadha, Mukhtar Ghaleb, Ahmed M. Shamsan Saleh

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The world witnessed a fierce attack from the Covid-19 virus, which affected public life socially, economically, healthily and psychologically. The world's governments tried to confront the pandemic by imposing a number of precautionary measures such as general closure, curfews and social distancing. Scientists have also made strenuous efforts to develop an effective vaccine to train the immune system to develop antibodies to combat the virus, thus reducing its symptoms and limiting its spread. Artificial intelligence, along with researchers and medical authorities, has accelerated the vaccine development process through big data processing and simulation. On the other hand, one of the most important negatives of the impact of Covid 19 was the state of anxiety and fear due to the blowout of rumors through social media, which prompted governments to try to reassure the public with the available means. This study aims to proposed using Sentiment Analysis (AKA Opinion Mining) and deep learning as efficient artificial intelligence techniques to work on retrieving the tweets of the public from Twitter and then analyze it automatically to extract their opinions, expression and feelings, negatively or positively, about the symptoms they may feel after vaccination. Sentiment analysis is characterized by its ability to access what the public post in social media within a record time and at a lower cost than traditional means such as questionnaires and interviews, not to mention the accuracy of the information as it comes from what the public expresses voluntarily.

Keywords: deep learning, opinion mining, natural language processing, sentiment analysis

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Authors: Ram Mohan, Richard Haney, Ajit Kelkar

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Current developments in computing have shown the advantage of using one or more Graphic Processing Units (GPU) to boost the performance of many computationally intensive applications but there are still limits to these GPU-enhanced systems. The major factors that contribute to the limitations of GPU(s) for High Performance Computing (HPC) can be categorized as hardware and software oriented in nature. Understanding how these factors affect performance is essential to develop efficient and robust applications codes that employ one or more GPU devices as powerful co-processors for HPC computational modeling. This research and technical presentation will focus on the analysis and understanding of the intrinsic interrelationship of both hardware and software categories on computational performance for single and multiple GPU-enhanced systems using a computationally intensive application that is representative of a large portion of challenges confronting modern HPC. The representative application uses unstructured finite element computations for transient composite resin infusion process flow modeling as the computational core, characteristics and results of which reflect many other HPC applications via the sparse matrix system used for the solution of linear system of equations. This work describes these various software and hardware factors and how they interact to affect performance of computationally intensive applications enabling more efficient development and porting of High Performance Computing applications that includes current, legacy, and future large scale computational modeling applications in various engineering and scientific disciplines.

Keywords: graphical processing unit, software development and engineering, performance analysis, system architecture and software performance

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Authors: Archana G. Lamdande, Shyam R. Garud, K. S. M. S. Raghavarao

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Coconut has two edible parts, that is, a white kernel (solid endosperm) and coconut water (liquid endosperm). The white kernel is generally used in fresh or dried form for culinary purposes. Coconut testa, is the brown skin, covering the coconut kernel. It is removed by paring of wet coconut and obtained as a by-product in coconut processing industries during the production of products such as desiccated coconut, coconut milk, whole coconut milk powder and virgin coconut oil. At present, it is used as animal feed component after drying and recovering the residual oil (by expelling). Experiments were carried out on expelling of coconut milk for shredded coconut with and without testa removal, in order to explore the possibility of increasing the milk yield and value addition in terms of increased polyphenol content. The color characteristics of coconut milk obtained from the grating without removal of testa were observed to be L* 82.79, a* 0.0125, b* 6.245, while that obtained from grating with removal of testa were L* 83.24, a* -0.7925, b* 3.1. A significant increase was observed in total phenol content of coconut milk obtained from the grating with testa (833.8 µl/ml) when compared to that from without testa (521.3 µl/ml). However, significant difference was not observed in protein content of coconut milk obtained from the grating with and without testa (4.9 and 5.0% w/w, respectively). Coconut milk obtained from grating without removal of testa showed higher milk yield (62% w/w) when compared to that obtained from grating with removal of testa (60% w/w). The fat content in coconut milk was observed to be 32% (w/w), and it is unstable due to such a high fat content. Therefore, several experiments were carried out for examining its stability by adjusting the fat content at different levels (32, 28, 24, and 20% w/w). It was found that the coconut milk was more stable with a fat content of 24 % (w/w). Homogenization and ultrasonication and their combinations were used for exploring the possibility of increasing the stability of coconut milk. The microscopic study was carried out for analyzing the size of fat globules and the degree of their uniform distribution.

Keywords: coconut milk, homogenization, stability, testa, ultrasonication

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Authors: Ji Zhou, Jung Hee Seo, Rajat Mittal

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Fish move in groups for foraging, reproduction, predator protection, and hydrodynamic efficiency. Schooling's predator protection involves the "many eyes" theory, which increases predator detection probability in a group. Reduced visual signature in a group scales with school size, offering per-capita protection. The ‘confusion effect’ makes it hard for predators to target prey in a group. These benefits, however, all focus on vision-based sensing, overlooking sound-based detection. Fish, including predators, possess sophisticated sensory systems for pressure waves and underwater sound. The lateral line system detects acoustic waves, while otolith organs sense infrasound, and sharks use an auditory system for low-frequency sounds. Among sound generation mechanisms of fish, the mechanism of dipole sound relates to hydrodynamic pressure forces on the body surface of the fish and this pressure would be affected by group swimming. Thus, swimming within a group could affect this hydrodynamic noise signature of fish and possibly serve as an additional protection afforded by schooling, but none of the studies to date have explored this effect. BAUVs with fin-like propulsors could reduce acoustic noise without compromising performance, addressing issues of anthropogenic noise pollution in marine environments. Therefore, in this study, we used our in-house immersed-boundary method flow and acoustic solver, ViCar3D, to simulate fish schools consisting of four swimmers in the classic ‘diamond’ configuration and discussed the feasibility of yielding higher swimming efficiency and controlling far-field sound signature of the school. We examine the effects of the relative phase of fin flapping of the swimmers and the simulation results indicate that the phase of the fin flapping is a dominant factor in both thrust enhancement and the total sound radiated into the far-field by a group of swimmers. For fish in the “diamond” configuration, a suitable combination of the relative phase difference between pairs of leading fish and trailing fish can result in better swimming performance with significantly lower hydroacoustic noise.

Keywords: fish schooling, biopropulsion, hydrodynamics, hydroacoustics

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Authors: Biswajit Pal, Amit Mallik, Anil K. Barik

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Current years have witnessed a phenomenal growth in the research on the rare earth-doped transparent host materials, the essential components in optoelectronics that meet up the increasing demand for fabrication of high quality optical devices especially in telecommunication system. The combination of low phonon energy (because of fluoride environment) and high chemical durability with superior mechanical stability (due to oxide environment) makes the oxyfluoride glass–ceramics the promising and useful materials in optoelectronics. The present work reports on the undoped and doped (1 mol% Pr2O3) glass ceramics of composition 16.52 Al2O3•1.5AlF3• 12.65LaF3•4.33Na2O•64.85 SiO2 (mol%), prepared by melting technique initially that follows annealation at 450 ºC for 1 h. The glass samples so obtained were heat treated at constant 600 ºC with a variation in heat treatment schedule (10- 80 h). TEM techniques were employed to structurally characterize the glass samples. Pr2O3 affects the phase separation in the glass and delays the onset of crystallization in the glass ceramic. The modified crystallization mechanism is established from the analysis of advanced STEM/EDXS results. The phase separated droplets after annealing turn into 10-20 nm of LaF3 nano crystals those upon scrutiny are found to be dotted with the doped Pr3+ ions within the crystals themselves. The EDXS results also suggest that the inner LaF3 crystal core is swallowed by an Al enriched layer that follows a Si enriched surrounding shell as the outer core. This greatly increases the viscosity in the periphery of the crystals that restricts further crystal growth to account for the formation of nano sized crystals.

Keywords: advanced STEM/EDXS, crystallization mechanism, nano crystals, pr3+ ion doped glass and glass ceramic, structural characterization

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Authors: Julian Wise

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Newcrest Mining is one of the world’s top five gold and rare earth mining organizations by production, reserves and market capitalization in the world. This paper elaborates on the data acquisition processes employed by Newcrest in collaboration with Fortune 500 listed organization, Insight Enterprises, to standardize machine learning solutions which process data from over a hundred thousand distributed Internet of Things (IoT) devices located at mine sites globally. Through the utilization of software architecture cloud technologies and edge computing, the technological developments enable for standardized processes of machine learning applications to influence the strategic optimization of mineral processing. Target objectives of the machine learning optimizations include time savings on mineral processing, production efficiencies, risk identification, and increased production throughput. The data acquired and utilized for predictive modelling is processed through edge computing by resources collectively stored within a data lake. Being involved in the digital transformation has necessitated the standardization software architecture to manage the machine learning models submitted by vendors, to ensure effective automation and continuous improvements to the mineral process models. Operating at scale, the system processes hundreds of gigabytes of data per day from distributed mine sites across the globe, for the purposes of increased improved worker safety, and production efficiency through big data applications.

Keywords: mineral technology, big data, machine learning operations, data lake

Procedia PDF Downloads 97

Authors: Bouayachi Ali, Alikouss Saida, Baroudi Zouhir, Zerhouni Youssef, Zouhair Mohammed, El Idrissi Assia, Essalhi Mourad

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The world-class Imiter silver deposit is located on the northern flank of the Precambrian Imiter buttonhole. This deposit is formed by epithermal veins hosted in the sandstone-pelite formations of the lower complex and in the basic conglomerates of the upper complex, these veins are controlled by a regional scale fault cluster, oriented N70°E to N90°E. The present work on the contribution of remote sensing on the geological mapping of the Imiter buttonhole and application to the mineralized structures of the Principal Corps B3. Mapping on satellite images is a very important tool in mineral prospecting. It allows the localization of the zones of interest in order to orientate the field missions by helping the localization of the major structures which facilitates the interpretation, the programming and the orientation of the mining works. The predictive map also allows for the correction of field mapping work, especially the direction and dimensions of structures such as dykes, corridors or scrapings. The use of a series of processing such as SAM, PCA, MNF and unsupervised and supervised classification on a Landsat 8 satellite image of the study area allowed us to highlight the main facies of the Imite area. To improve the exploration research, we used another processing that allows to realize a spatial distribution of the alteration mineral indices, and the application of several filters on the different bands to have lineament maps.

Keywords: principal corps B3, teledetection, Landsat 8, Imiter II, silver mineralization, lineaments

Procedia PDF Downloads 82

Authors: O. Delage, H. Bencherif, T. Portafaix, A. Bourdier

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The main purpose of time series analysis is to learn about the dynamics behind some time ordered measurement data. Two approaches are used in the literature to get a better knowledge of the dynamics contained in observation data sequences. The first of these approaches concerns time series decomposition, which is an important analysis step allowing patterns and behaviors to be extracted as components providing insight into the mechanisms producing the time series. As in many cases, time series are short, noisy, and non-stationary. To provide components which are physically meaningful, methods such as Empirical Mode Decomposition (EMD), Empirical Wavelet Transform (EWT) or, more recently, Empirical Adaptive Wavelet Decomposition (EAWD) have been proposed. The second approach is to reconstruct the dynamics underlying the time series as a trajectory in state space by mapping a time series into a set of Rᵐ lag vectors by using the method of delays (MOD). Takens has proved that the trajectory obtained with the MOD technic is equivalent to the trajectory representing the dynamics behind the original time series. This work introduces the singular spectrum decomposition (SSD), which is a new adaptive method for decomposing non-linear and non-stationary time series in narrow-banded components. This method takes its origin from singular spectrum analysis (SSA), a nonparametric spectral estimation method used for the analysis and prediction of time series. As the first step of SSD is to constitute a trajectory matrix by embedding a one-dimensional time series into a set of lagged vectors, SSD can also be seen as a reconstruction method like MOD. We will first give a brief overview of the existing decomposition methods (EMD-EWT-EAWD). The SSD method will then be described in detail and applied to experimental time series of observations resulting from total columns of ozone measurements. The results obtained will be compared with those provided by the previously mentioned decomposition methods. We will also compare the reconstruction qualities of the observed dynamics obtained from the SSD and MOD methods.

Keywords: time series analysis, adaptive time series decomposition, wavelet, phase space reconstruction, singular spectrum analysis

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Authors: Revoti Prasad Bora, Saurabh Yadav, Nikita Katyal

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In the context of educational data mining, the use case of extracting information from images containing both text and diagrams is of high importance. Hence, document analysis requires the extraction of diagrams from such images and processes the text and diagrams separately. To the author’s best knowledge, none among plenty of approaches for extracting tables, figures, etc., suffice the need for real-time processing with high accuracy as needed in multiple applications. In the education domain, diagrams can be of varied characteristics viz. line-based i.e. geometric diagrams, chemical bonds, mathematical formulas, etc. There are two broad categories of approaches that try to solve similar problems viz. traditional computer vision based approaches and deep learning approaches. The traditional computer vision based approaches mainly leverage connected components and distance transform based processing and hence perform well in very limited scenarios. The existing deep learning approaches either leverage YOLO or faster-RCNN architectures. These approaches suffer from a performance-accuracy tradeoff. This paper proposes a U-Net based architecture that formulates the diagram extraction as a segmentation problem. The proposed method provides similar accuracy with a much faster extraction time as compared to the mentioned state-of-the-art approaches. Further, the segmentation mask in this approach allows the extraction of diagrams of irregular shapes.

Keywords: computer vision, deep-learning, educational data mining, faster-RCNN, figure extraction, image segmentation, real-time document analysis, text extraction, U-Net, YOLO

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Authors: Rui Lin, Jimmy Xiangji Huang, Gary Spraakman

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This forthcoming systematic review will underscore the imperative of leveraging technology to mitigate social isolation in older adults, particularly in the context of unprecedented global challenges such as the COVID-19 pandemic. With the continual evolution of technology, it becomes crucial to scrutinize the efficacy of interventions and discern how they can alleviate social isolation and augment social well-being among the elderly. This review will strive to clarify the best methods for older adults to utilize cost-effective and user-friendly technology and will investigate how the adaptation and execution of such interventions can be fine-tuned to maximize their positive outcomes. The study will follow the Preferred Reporting Items for Systematic Reviews and Meta-Analyses guidelines to filter pertinent studies. We foresee conducting an analysis of articles and executing a narrative analysis to discover themes and indicators related to quality of life and, technology use and well-being. The review will examine how involving older adults at the community level, applying top practices from community-based participatory research, can establish efficient strategies to implement technology-based interventions designed to diminish social isolation and boost digital use self-efficacy. Applications based on mobile technology and virtual platforms are set to assume a crucial role not only in enhancing connections within families but also in connecting older adults to vital healthcare resources, fostering both physical and mental well-being. The review will investigate how technological devices and platforms can address the cognitive, visual, and auditory requirements of older adults, thus strengthening their confidence and proficiency in digital use—a crucial factor during enforced social distancing or self-isolation periods during pandemics. This review will endeavor to provide insights into the multifaceted benefits of technology for older adults, focusing on how tailored technological interventions can be a beacon of social and mental wellness in times of social restrictions. It will contribute to the growing body of knowledge on the intersection of technology and elderly well-being, offering nuanced understandings and practical implications for developing user-centric, effective, and inclusive technological solutions for older populations.

Keywords: older adults, health service delivery, digital health, social isolation, social well-being

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Authors: Manjitsingh Rajput

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Visual communication plays an important role in artificial intelligence (AI) because it enables machines to understand and interpret visual information, similar to how humans do. This abstract explores the importance of visual communication in AI and emphasizes the importance of various applications such as computer vision, object emphasis recognition, image classification and autonomous systems. In going deeper, with deep learning techniques and neural networks that modify visual understanding, In addition to AI programming, the abstract discusses challenges facing visual interfaces for AI, such as data scarcity, domain optimization, and interpretability. Visual communication and other approaches, such as natural language processing and speech recognition, have also been explored. Overall, this abstract highlights the critical role that visual communication plays in advancing AI capabilities and enabling machines to perceive and understand the world around them. The abstract also explores the integration of visual communication with other modalities like natural language processing and speech recognition, emphasizing the critical role of visual communication in AI capabilities. This methodology explores the importance of visual communication in AI development and implementation, highlighting its potential to enhance the effectiveness and accessibility of AI systems. It provides a comprehensive approach to integrating visual elements into AI systems, making them more user-friendly and efficient. In conclusion, Visual communication is crucial in AI systems for object recognition, facial analysis, and augmented reality, but challenges like data quality, interpretability, and ethics must be addressed. Visual communication enhances user experience, decision-making, accessibility, and collaboration. Developers can integrate visual elements for efficient and accessible AI systems.

Keywords: visual communication AI, computer vision, visual aid in communication, essence of visual communication.

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Authors: Shutchapol Chopvitayakun

Abstract:

Nowadays, especially for the last 5 years, mobile devices, mobile applications and mobile users, through the deployment of wireless communication and mobile phone cellular network, all these components are growing significantly bigger and stronger. They are being integrated into each other to create multiple purposes and pervasive deployments into every business and non-business sector such as education, medicine, traveling, finance, real estate and many more. Objective of this study was to develop a mobile application for seniors or last-year students who enroll the internship program at each tertiary school (undergraduate school) and do onsite practice at real field sties, real organizations and real workspaces. During the internship session, all students as the interns are required to exercise, drilling and training onsite with specific locations and specific tasks or may be some assignments from their supervisor. Their work spaces are both private and government corporates and enterprises. This mobile application is developed under schema of a transactional processing system that enables users to keep daily work or practice log, monitor true working locations and ability to follow daily tasks of each trainee. Moreover, it provides useful guidance from each intern’s advisor, in case of emergency. Finally, it can summarize all transactional data then calculate each internship cumulated hours from the field practice session for each individual intern.

Keywords: internship, mobile application, Android OS, smart phone devices, mobile transactional processing system, guidance and monitoring, tertiary education, senior students, model view controller (MVC)

Procedia PDF Downloads 298

Authors: N. Boudinar, A. Djekoun, A. Otmani, B. Bouzabata, J. M. Greneche

Abstract:

High-energy ball milling is a solid-state powder processing technique that allows synthesizing a variety of equilibrium and non-equilibrium alloy phases starting from elemental powders. The advantage of this process technology is that the powder can be produced in large quantities and the processing parameters can be easily controlled, thus it is a suitable method for commercial applications. It can also be used to produce amorphous and nanocrystalline materials in commercially relevant amounts and is also amenable to the production of a variety of alloy compositions. Mechanical alloying (high-energy ball milling) provides an inter-dispersion of elements through a repeated cold welding and fracture of free powder particles; the grain size decreases to nano metric scale and the element mix together. Progressively, the concentration gradients disappear and eventually the elements are mixed at the atomic scale. The end products depend on many parameters such as the milling conditions and the thermodynamic properties of the milled system. Here, the mechanical alloying technique has been used to prepare nano crystalline Fe_50 and Fe_64 wt.% Ni alloys from powder mixtures. Scanning electron microscopy (SEM) with energy-dispersive, X-ray analyses and Mössbauer spectroscopy were used to study the mixing at nanometric scale. The Mössbauer Spectroscopy confirmed the ferromagnetic ordering and was use to calculate the distribution of hyperfin field. The Mössbauer spectrum for both alloys shows the existence of a ferromagnetic phase attributed to γ-Fe-Ni solid solution.

Keywords: nanocrystalline, mechanical alloying, X-ray diffraction, Mössbauer spectroscopy, phase transformations

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Authors: Prodipta Bhowmik, Poulami Saha, Preety Mehra, Yogesh Soni, Triloki Nath Jha

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In India, the smart city concept is growing day by day. So, for smart city development, a better traffic management and monitoring system is a very important requirement. Nowadays, road accidents increase due to more vehicles on the road. Reckless driving is mainly responsible for a huge number of accidents. So, an efficient traffic management system is required for all kinds of roads to control the traffic speed. The speed limit varies from road to road basis. Previously, there was a radar system but due to high cost and less precision, the radar system is unable to become favorable in a traffic management system. Traffic management system faces different types of problems every day and it has become a researchable topic on how to solve this problem. This paper proposed a computer vision and machine learning-based automated system for multiple vehicle detection, tracking, and speed estimation of vehicles using image processing. Detection of vehicles and estimating their speed from a real-time video is tough work to do. The objective of this paper is to detect vehicles and estimate their speed as accurately as possible. So for this, a real-time video is first captured, then the frames are extracted from that video, then from that frames, the vehicles are detected, and thereafter, the tracking of vehicles starts, and finally, the speed of the moving vehicles is estimated. The goal of this method is to develop a cost-friendly system that can able to detect multiple types of vehicles at the same time.

Keywords: OpenCV, Haar Cascade classifier, DLIB, YOLOV3, centroid tracker, vehicle detection, vehicle tracking, vehicle speed estimation, computer vision

Procedia PDF Downloads 63

Authors: A. Zh. Aupova, A. Ulankyzy, A. Sarsenova, A. Kussayin, Sh. Turarbek, N. Moldagulova, A. Kurmanbayev

Abstract:

One of the methods of organic waste bioconversion into environmentally-friendly fertilizer is composting. Microorganisms that produce hydrolytic enzymes play a significant role in accelerating the process of organic waste composting. We studied the enzymatic potential (amylase, protease, cellulase, lipase, urease activity) of bacteria isolated from the sewage sludge of Nur-Sultan, Rudny, and Fort-Shevchenko cities, the dacha soil of Nur-Sultan city, and freshly cut grass from the dacha for processing organic waste and identifying active strains. Microorganism isolation was carried out by the cultures enrichment method on liquid nutrient media, followed by inoculating on different solid media to isolate individual colonies. As a result, sixty-one microorganisms were isolated, three of which were thermophiles (DS1, DS2, and DS3). The highest number of isolates, twenty-one and eighteen, were isolated from sewage sludge of Nur-Sultan and Rudny cities, respectively. Ten isolates were isolated from the wastewater of the sewage treatment plant in Fort-Shevchenko. From the dacha soil of Nur-Sultan city and freshly cut grass - 9 and 5 isolates were revealed, respectively. The lipolytic, proteolytic, amylolytic, cellulolytic, ureolytic, and oil-oxidizing activities of isolates were studied. According to the results of experiments, starch hydrolysis (amylolytic activity) was found in 2 isolates - CB2/2, and CB2/1. Three isolates - CB2, CB2/1, and CB1/1 were selected for the highest ability to break down casein. Among isolated 61 bacterial cultures, three isolates could break down fats - CB3, CBG1/1, and IL3. Seven strains had cellulolytic activity - DS1, DS2, IL3, IL5, P2, P5, and P3. Six isolates rapidly decomposed urea. Isolate P1 could break down casein and cellulose. Isolate DS3 was a thermophile and had cellulolytic activity. Thus, based on the conducted studies, 15 isolates were selected as a potential for sewage sludge composting - CB2, CB3, CB1/1, CB2/2, CBG1/1, CB2/1, DS1, DS2, DS3, IL3, IL5, P1, P2, P5, P3. Selected strains were identified on a mass spectrometer (Maldi-TOF). The isolate - CB 3 was referred to the genus Rhodococcus rhodochrous; two isolates CB2 and CB1 / 1 - to Bacillus cereus, CB 2/2 - to Cryseobacterium arachidis, CBG 1/1 - to Pseudoxanthomonas sp., CB2/1 - to Bacillus megaterium, DS1 - to Pediococcus acidilactici, DS2 - to Paenibacillus residui, DS3 - to Brevibacillus invocatus, three strains IL3, P5, P3 - to Enterobacter cloacae, two strains IL5, P2 - to Ochrobactrum intermedium, and P1 - Bacillus lichenoformis. Hence, 60 isolates were isolated from the wastewater of the cities of Nur-Sultan, Rudny, Fort-Shevchenko, the dacha soil of Nur-Sultan city, and freshly cut grass from the dacha. Based on the highest enzymatic activity, 15 active isolates were selected and identified. These strains may become the candidates for bio preparation for sewage sludge processing.

Keywords: sewage sludge, composting, bacteria, enzymatic activity

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Authors: Vedansh Gupta, Allyson Lutz, Ameen Razavi, Fatemeh Shirazi

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The agriculture industry is especially vulnerable to forecasted water shortages. In the fresh and fresh-cut produce sector, conventional flume-based washing with recirculation exhibits high water demand. This leads to a large water footprint and possible cross-contamination of pathogens. These can be alleviated through advanced water reuse processes, such as membrane technologies including reverse osmosis (RO). Water reuse technologies effectively remove dissolved constituents but can easily foul without pre-treatment. Biological treatment is effective for the removal of organic compounds responsible for fouling, but not at the low temperatures encountered at most produce processing facilities. This study showed that the Microvi MicroNiche Engineering (MNE) technology effectively removes organic compounds (> 80%) at low temperatures (6-8 °C) from wash water. The MNE technology uses synthetic microorganism-material composites with negligible solids production, making it advantageously situated as an effective bio-pretreatment for RO. A preliminary technoeconomic analysis showed 60-80% savings in operation and maintenance costs (OPEX) when using the Microvi MNE technology for organics removal. This study and the accompanying economic analysis indicated that the proposed technology process will substantially reduce the cost barrier for adopting water reuse practices, thereby contributing to increased food safety and furthering sustainable water reuse processes across the agricultural industry.

Keywords: biological pre-treatment, innovative technology, vegetable processing, water reuse, agriculture, reverse osmosis, MNE biocatalysts

Procedia PDF Downloads 115

Authors: James Banda, Jupiter Simbeye, Essau Chisale, Geoffrey Kanyerere, Kings Kamtambe

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Improved solar tent dryers for processing small fish species were designed to reduce post-harvest fish losses and improve supply of quality fish products in the southern part of Lake Malawi under CultiAF project. A comparative analysis of the quality of Diplotaxodon (Ndunduma) from Lake Malawi processed in solar tent dryer and open sun drying was conducted using proximate analysis, microbial analysis and sensory evaluation. Proximates for solar tent dried fish and open sun dried fish in terms of proteins, fats, moisture and ash were 63.3±0.15% and 63.3±0.34%, 19.6±0.09% and 19.9±0.25%, 8.3±0.12% and 17.0±0.01%, and 15.6±0.61% and 21.9±0.91% respectively. Crude protein and crude fat showed non-significant differences (p = 0.05), while moisture and ash content were significantly different (p = 001). Open sun dried fish had significantly higher numbers of viable bacteria counts (5.2×10⁶ CFU) than solar tent dried fish (3.9×10² CFU). Most isolated bacteria from solar tent dried and open sun dried fish were 1.0×10¹ and 7.2×10³ for Total coliform, 0 and 4.5 × 10³ for Escherishia coli, 0 and 7.5 × 10³ for Salmonella, 0 and 5.7×10² for shigella, 4.0×10¹ and 6.1×10³ for Staphylococcus, 1.0×10¹ and 7.0×10² for vibrio. Qualitative evaluation of sensory properties showed higher acceptability of 3.8 for solar tent dried fish than 1.7 for open sun dried fish. It is concluded that promotion of solar tent drying in processing small fish species in Malawi would support small-scale fish processors to produce quality fish in terms of nutritive value, reduced microbial contamination, sensory acceptability and reduced moisture content.

Keywords: diplotaxodon, Malawi, open sun drying, solar tent drying

Procedia PDF Downloads 312

Authors: Zhang Songning, Guan Zheng, Ci Yan, Ding Gangyi

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The application of physical simulation engines in collaborative editing systems has an important background and role. Firstly, physical simulation engines can provide real-world physical simulations, enabling users to interact and collaborate in real time in virtual environments. This provides a more intuitive and immersive experience for collaborative editing systems, allowing users to more accurately perceive and understand various elements and operations in collaborative editing. Secondly, through physical simulation engines, different users can share virtual space and perform real-time collaborative editing within it. This real-time sharing and collaborative editing method helps to synchronize information among team members and improve the efficiency of collaborative work. Through experiments, the average model transmission speed of a single person in the collaborative editing system has increased by 141.91%; the average model processing speed of a single person has increased by 134.2%; the average processing flow rate of a single person has increased by 175.19%; the overall efficiency improvement rate of a single person has increased by 150.43%. With the increase in the number of users, the overall efficiency remains stable, and the physical simulation engine running status collaborative editing system also has horizontal scalability. It is not difficult to see that the design and implementation of a collaborative editing system based on physical simulation engines not only enriches the user experience but also optimizes the effectiveness of team collaboration, providing new possibilities for collaborative work.

Keywords: physics engine, simulation technology, collaborative editing, system design, data transmission

Procedia PDF Downloads 59

Authors: Farina Riaz, Shahab Abdulla, Srinjoy Ganguly, Hajime Suzuki, Ravinesh C. Deo, Susan Hopkins

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Recently, quantum machine learning has received significant attention. For various types of data, including text and images, numerous quantum machine learning (QML) models have been created and are being tested. Images are exceedingly complex data components that demand more processing power. Despite being mature, classical machine learning still has difficulties with big data applications. Furthermore, quantum technology has revolutionized how machine learning is thought of, by employing quantum features to address optimization issues. Since quantum hardware is currently extremely noisy, it is not practicable to run machine learning algorithms on it without risking the production of inaccurate results. To discover the advantages of quantum versus classical approaches, this research has concentrated on colored image data. Deep learning classification models are currently being created on Quantum platforms, but they are still in a very early stage. Black and white benchmark image datasets like MNIST and Fashion MINIST have been used in recent research. MNIST and CIFAR-10 were compared for binary classification, but the comparison showed that MNIST performed more accurately than colored CIFAR-10. This research will evaluate the performance of the QML algorithm on the colored benchmark dataset CIFAR-10 to advance QML's real-time applicability. However, deep learning classification models have not been developed to compare colored images like Quantum Convolutional Neural Network (QCNN) to determine how much it is better to classical. Only a few models, such as quantum variational circuits, take colored images. The methodology adopted in this research is a hybrid approach by using penny lane as a simulator. To process the 10 classes of CIFAR-10, the image data has been translated into grey scale and the 28 × 28-pixel image containing 10,000 test and 50,000 training images were used. The objective of this work is to determine how much the quantum approach can outperform a classical approach for a comprehensive dataset of color images. After pre-processing 50,000 images from a classical computer, the QCNN model adopted a hybrid method and encoded the images into a quantum simulator for feature extraction using quantum gate rotations. The measurements were carried out on the classical computer after the rotations were applied. According to the results, we note that the QCNN approach is ~12% more effective than the traditional classical CNN approaches and it is possible that applying data augmentation may increase the accuracy. This study has demonstrated that quantum machine and deep learning models can be relatively superior to the classical machine learning approaches in terms of their processing speed and accuracy when used to perform classification on colored classes.

Keywords: CIFAR-10, quantum convolutional neural networks, quantum deep learning, quantum machine learning

Procedia PDF Downloads 106

Authors: Martin H¨ausl, Maximilian Auch, Johannes Forster, Peter Mandl, Alexander Schill

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In order to survive on the market, companies must constantly develop improved and new products. These products are designed to serve the needs of their customers in the best possible way. The creation of new products is also called innovation and is primarily driven by a company’s internal research and development department. However, a new approach has been taking place for some years now, involving external knowledge in the innovation process. This approach is called open innovation and identifies customer knowledge as the most important source in the innovation process. This paper presents a concept of using social media posts as an external source to support the open innovation approach in its initial phase, the Ideation phase. For this purpose, the social media posts are semantically structured with the help of an ontology and the authors are evaluated using graph-theoretical metrics such as density. For the structuring and evaluation of relevant social media posts, we also use the findings of Natural Language Processing, e. g. Named Entity Recognition, specific dictionaries, Triple Tagger and Part-of-Speech-Tagger. The selection and evaluation of the tools used are discussed in this paper. Using our ontology and metrics to structure social media posts enables users to semantically search these posts for new product ideas and thus gain an improved insight into the external sources such as customer needs.

Keywords: idea ontology, innovation management, semantic search, open information extraction

Procedia PDF Downloads 174

Authors: Amina Farooq, Nauman Zafar Butt

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This paper is about methods and tools for counting particles of interest, such as cells. A microfluidic system with interconnected electronics on a flexible substrate, inlet-outlet ports and interface schemes, sensitive and selective detection of cells specificity, and processing of cell counting at polymer interfaces in a microscale biosensor for use in the detection of target biological and non-biological cells. The development of fluidic channels, planar fluidic contact ports, integrated metal electrodes on a flexible substrate for impedance measurements, and a surface modification plasma treatment as an intermediate bonding layer are all part of the fabrication process. Magnetron DC sputtering is used to deposit a double metal layer (Ti/Pt) over the polypropylene film. Using a photoresist layer, specified and etched zones are established. Small fluid volumes, a reduced detection region, and electrical impedance measurements over a range of frequencies for cell counts improve detection sensitivity and specificity. The procedure involves continuous flow of fluid samples that contain particles of interest through the microfluidic channels, counting all types of particles in a portion of the sample using the electrical differential counter to generate a bipolar pulse for each passing cell—calculating the total number of particles of interest originally in the fluid sample by using MATLAB program and signal processing. It's indeed potential to develop a robust and economical kit for cell counting in whole-blood samples using these methods and similar devices.

Keywords: impedance, biochip, cell counting, microfluidics

Procedia PDF Downloads 150

Authors: Dilshad Ali Mohammed, Ziyad Nayef Shamsulddin Aldoski, Millet Salim Mohammed

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The increase in levels of traffic congestion along urban signalized arterials needs efficient traffic management. The application of traffic signal coordination can improve the traffic operation and safety for a series of signalized intersection along the arterials. The objective of this study is to evaluate the benefits achievable through actuated traffic signal coordination and make a comparison in control delay against the same signalized intersection in case of being isolated. To accomplish this purpose, a series of eight signalized intersections located on two major arterials in Duhok City was chosen for conducting the study. Traffic data (traffic volumes, link and approach speeds, and passenger car equivalent) were collected at peak hours. Various methods had been used for collecting data such as video recording technique, moving vehicle method and manual methods. Geometric and signalization data were also collected for the purpose of the study. The coupling index had been calculated to check the coordination attainability, and then time space diagrams were constructed representing one-way coordination for the intersections on Barzani and Zakho Streets, and others represented two-way coordination for the intersections on Zakho Street with accepted progression bandwidth efficiency. The results of this study show great progression bandwidth of 54 seconds for east direction coordination and 17 seconds for west direction coordination on Barzani Street under suggested controlled speed of 60 kph agreeable with the present data. For Zakho Street, the progression bandwidth is 19 seconds for east direction coordination and 18 seconds for west direction coordination under suggested controlled speed of 40 kph. The results show that traffic signal coordination had led to high reduction in intersection control delays on both arterials.

Keywords: bandwidth, congestion, coordination, traffic, signals, streets

Procedia PDF Downloads 282

Authors: Shahad Nagoor, Lucy Hederman, Kevin Koidl, Annalina Caputo

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Doctors’ notes reflect their impressions, attitudes, clinical sense, and opinions about patients’ conditions and progress, and other information that is essential for doctors’ daily clinical decisions. Despite their value, clinical notes are insufficiently researched within the language processing community. Automatically extracting information from unstructured text data is known to be a difficult task as opposed to dealing with structured information such as vital physiological signs, images, and laboratory results. The aim of this research is to investigate how Natural Language Processing (NLP) techniques and machine learning techniques applied to clinician notes can assist in doctors’ decision-making in Intensive Care Unit (ICU) for coronavirus disease 2019 (COVID-19) patients. The hypothesis is that clinical outcomes like survival or mortality can be useful in influencing the judgement of clinical sentiment in ICU clinical notes. This paper introduces two contributions: first, we introduce COVID_ICU_BERT, a fine-tuned version of clinical transformer models that can reliably predict clinical sentiment for notes of COVID patients in the ICU. We train the model on clinical notes for COVID-19 patients, a type of notes that were not previously seen by clinicalBERT, and Bio_Discharge_Summary_BERT. The model, which was based on clinicalBERT achieves higher predictive accuracy (Acc 93.33%, AUC 0.98, and precision 0.96 ). Second, we perform data augmentation using clinical contextual word embedding that is based on a pre-trained clinical model to balance the samples in each class in the data (survived vs. deceased patients). Data augmentation improves the accuracy of prediction slightly (Acc 96.67%, AUC 0.98, and precision 0.92 ).

Keywords: BERT fine-tuning, clinical sentiment, COVID-19, data augmentation

Procedia PDF Downloads 184

Authors: Néstor Iván Rojas, Wilson Medina Sierra

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Managing spatial information is described through a Geographic Information System (GIS), for some neighborhoods in the city of Tunja, in relation to the structural typology of the buildings. The use of GIS provides tools that facilitate the capture, processing, analysis and dissemination of cartographic information, product quality evaluation of the classification of buildings. Allows the development of a method that unifies and standardizes processes information. The project aims to generate a geographic database that is useful to the entities responsible for planning and disaster prevention and care for vulnerable populations, also seeks to be a basis for seismic vulnerability studies that can contribute in a study of urban seismic microzonation. The methodology consists in capturing the plat including road naming, neighborhoods, blocks and buildings, to which were added as attributes, the product of the evaluation of each of the housing data such as the number of inhabitants and classification, year of construction, the predominant structural systems, the type of mezzanine board and state of favorability, the presence of geo-technical problems, the type of cover, the use of each building, damage to structural and non-structural elements . The above data are tabulated in a spreadsheet that includes cadastral number, through which are systematically included in the respective building that also has that attribute. Geo-referenced data base is obtained, from which graphical outputs are generated, producing thematic maps for each evaluated data, which clearly show the spatial distribution of the information obtained. Using GIS offers important advantages for spatial information management and facilitates consultation and update. Usefulness of the project is recognized as a basis for studies on issues of planning and prevention.

Keywords: microzonation, buildings, geo-processing, cadastral number

Procedia PDF Downloads 318